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Modeling and Optimization of copper flash smelting Process Based on Neural Network

过程工程学报 2008年第S1期8卷 105-109页

作者：汪金良张传福曾青云童长仁张文海 School of Metallurgical Science and Engineering Central South UniversityChangshaHunan 410083China Faculty of Material and Chemistry EngineeringJiangxi University of Science and TechnologyGanzhouJiangxi 341000China School of Metallurgical Science and Engineering Central South UniversityChangshaHunan 410083China Faculty of Material and Chemistry Engineering Jiangxi University of Science and TechnologyGanzhouJiangxi 341000China China Nerin Engineering Co. Ltd.NanchangJiangxi 330002China

关键词： neural network genetic algorithm copper flash smelting modeling optimization

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Grey correlation analysis of factors influencing maldistribution in feeding device of copper flash smelting

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Journal of Central South University 2012年第7期19卷 1938-1945页

作者：周萍尧颖瑾艾元方刘安明徐则林谢剑才 School of Energy Science and Engineering Central South University Jinlong copper Co. Ltd.

An experimental model of maldistribution was established and grey correlation analysis method was employed to describe quantitatively the maldistribution phenomenon in the feeding device of copper flash *** motion in the feeding device was separated into uniform flow in chute and restricted slanting parabolic motion in distributor *** affecting particle velocity at the chute outlet and particle moving distance in the distributor channel,which also cause the maldistribution,were analyzed based on the assumption of pseudo *** were conducted to study the maldistribution using river *** results indicate obvious mass maldistribution and an even higher degree with the increase of feeding mass rate;meanwhile,size maldistribution is ***,feeding intensity has a larger impact on circumferential maldistribution than on radial *** on the experimental results of the eight factors impacting the maldistribution,grey relation of each factor was calculated using grey correlation *** importances of these factors were *** results show that a proper adjustment of the structure will ameliorate the maldistribution phenomenon in the feeding device of copper flash smelting.

关键词： particle maldistribution grey correlation pseudo fluid copper flash smelting

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Modeling and Optimization of copper flash smelting Process Based on Neural Network

Modeling and Optimization of Copper Flash Smelting Process B...

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2008年全国冶金物理化学学术会议

作者：汪金良张传福曾青云童长仁张文海 School of Metallurgical Science and Engineering Central South University Faculty of Material and Chemistry Engineering Jiangxi University of Science and Technology China Nerin Engineering Co. Ltd.

The copper flash smelting process neural network model(CFSPNNM)was developed,its input layer includes eight nodes:oxygen grade(OG),oxygen volume per ton of concentrate(OVPTC),flux rate(FR)and quantities of Cu,S,Fe,SiO and MgO in copper concentrate;output layer includes three nodes:matte grade,matte temperature and Fe/SiO in slag,and net structure was ***,the internal relationship between the technological parameters and the objective parameters was built after the CFSPNNM was trained by using GA-BP ***,the technological parameters were optimized by using genetic algorithms(GA)to make energy consumption the *** results showed that the CFSPNNM had high prediction precision and good generalization *** with the practical average data,the energy consumption can be reduced by 6.8% if the smelting process is controlled by adopting the optimized technological parameters.

关键词： neural network genetic algorithm copper flash smelting modeling optimization

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Online monitoring and assessment of energy efficiency for copper smelting process

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Journal of Central South University 2019年第8期26卷 2149-2159页

作者： CHEN Zhuo ZHU Zhen-yu WANG Xiao-na SONG Yan-po School of Energy Science and Engineering Central South University

The copper flash smelting process is characterized by its involvement of wide energy sources and high energy consumption, so the energy conservation is usually a highly concerned topic for the flash smelting enterprises. However, due to the complexity of the system, it is quite difficult to perform a timely comprehensive analysis of the energy consumption of the whole production system. Aiming to realize an online assessment of the energy consumption of the system, great effort was first made in Jinguan copper, Tongling Nonferrous Metals Group Co. Ltd. Methods were proposed to solve technical difficulties such as the acquisition and processing of data with different sampling frequencies, the online evaluation of the electricity consumption, and timely evaluation of product output in the periodic process. As a result, a software system was developed to make the online analysis of the energy consumption and efficiency from the three levels ranging from the system to the equipment. The analytical results at the system level was introduce. It’s found that electricity is the most consumed energy in the system, accounting for 77.3% of the total energy consumption. The smelting unit has the highest energy consumption, accounting for 52.8% of the total energy consumed in the whole enterprise.

关键词： energy consumption energy efficiency online assessment copper flash smelting

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